1. Field of the Invention
The present invention relates to signal and data processing systems. More specifically, the present invention provides a system for recomposing an image from an encoded signal.
2. Background
As the transmission size or transmission rate of video data increases, the need for effective and efficient compression and decompression of the video data becomes more important. Various types of image processing systems are available for encoding and decoding images.
Certain image processing systems use techniques involving wavelet technology. A wavelet transforms an image into multiple frequency bands. Each frequency band contains the image at a quarter resolution of the original image, in varying degrees of image quality. As the bands progress from a low frequency to a high frequency, the image quality increases. The lowest frequency band is generally the most important band for visual sensitivity. Therefore, the lowest frequency band is typically the first band transmitted, and the highest frequency band is typically the last band transmitted. Thus, if only the low frequency band is received, the major features of the image are visible even though the information contained in the remaining higher frequency bands is not displayed.
When wavelet techniques are used in a CODEC (COder-DECoder) system, the CODEC consists of a wavelet decomposition module that breaks the image into multiple bands and a wavelet recomposition module that transforms the multiple bands into the image with original resolution.
A wavelet decomposition module calculates a particular pixel value by performing filtering in the neighborhood of pixels surrounding the particular pixel. This filtering is performed in both a horizontal direction and a vertical direction. Similarly, a wavelet recomposition module performs filtering as part of the recomposition process.
In existing systems, the wavelet recomposition filtering process is performed sequentially in two separate steps. First, filtering is performed in one dimension(e.g., horizontally). Next, filtering is performed in a second dimension (e.g., vertically). These existing recomposition modules are calculation-intensive and require two separate passes through the data, which does not effectively utilize cache memory in typical computer systems. Thus, these existing recomposition modules are expensive in terms of Central Processing Unit (CPU) execution time.
It is therefore desirable to provide a wavelet recomposition module capable of efficiently recomposing a wavelet and reconstructing an image from a plurality of bands of data, without the above problems.